Neural diversity impacts how the brain processes information

Northwestern Medicine researchers have revealed new insights into the impact of neuronal structural diversity on neuronal computation, the basis of brain function, according to a recent study published in the Proceedings of the National Academy of Sciences.

The nervous system is made up of a network of interacting neural networks that filter, store, and transform information about a person’s internal and external states. The networks that provide this information processing are made up of very diverse cells, with neurons varying in terms of structure, genetic expression and electrical properties.

This structural and genetic diversity among these neurons causes them to produce varied responses to inputs, but the exact impact of this diversity on overall computation and information processing in larger neural networks remains poorly understood.

“Although there is a growing body of research aimed at identifying and understanding neuronal cell types, mathematical models of the brain generally neglect this diversity,” said Ann Kennedy, Ph.D., assistant professor of neuroscience and author principal of the study.

In the current study, researchers used a new mathematical model to introduce diversity into a neural network by adding variation to neuronal spiking thresholds, an electrical property that determines when a neuron “spikes” and sends an output to neurons. neighbors. Based on this model, investigators examined how increasing the diversity of spike thresholds in a network affected the network’s ability to control, encode, and decode information.

The researchers found that adjusting the diversity of spike thresholds supports different computational functions, depending on how a neuron communicates with its neighboring neurons. Specifically, in neurons that suppressed spikes from their neighbors, changing the diversity of spike thresholds determined the extent to which cells could control the flow of information in a network.

Furthermore, according to the authors, reducing this diversity too much could lead to crisis-like events that would dominate network activity.

In other populations of neurons, they found that increasing the diversity of spike thresholds helped neural networks precisely control their activity, which is important for everyday functions such as movement control. Conversely, reducing this diversity improved the network’s ability to solve problems requiring short-term memory.

“It is not that greater heterogeneity is always beneficial for the functioning of a neuronal population, but we must take it into account in order to understand how a particular level of heterogeneity that we observe when we record a neuronal population in “The brain translates into functional capacity in this population,” said Richard Gast, Ph.D., a postdoctoral researcher in the Kennedy lab and lead author of the study.

According to Gast, the results also have the potential to direct neuroscientists toward using models that account for neuronal heterogeneity in neural networks. He added that in the future, the team will apply their mathematical model to study the role that neuronal diversity plays in the basal ganglia, a part of the brain heavily affected by Parkinson’s disease.

“If we simply ignore the heterogeneity of the basal ganglia and model it mathematically, our results suggest that we will get functional properties of neuronal populations in the basal ganglia that are very wrong, so this is certainly an important variable to consider here “, Gast said.